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Alexander C. — Market Models: A Guide to Financial Data Analysis
Alexander C. — Market Models: A Guide to Financial Data Analysis



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Íàçâàíèå: Market Models: A Guide to Financial Data Analysis

Àâòîð: Alexander C.

Àííîòàöèÿ:

Market Models provides an authoritative and up-to-date treatment of the use of market data to develop models for financial analysis. Written by a leading figure in the field of financial data analysis, this book is the first of its kind to address the vital techniques required for model selection and development. Model developers are faced with many decisions, about the pricing, the data, the statistical methodology and the calibration and testing of the model prior to implementation. It is important to make the right choices and Carol Alexander's clear exposition provides valuable insights at every stage.
In each of the 13 Chapters, Market Models presents real world illustrations to motivate theoretical developments. The accompanying CD contains spreadsheets with data and programs; this enables you to implement and adapt many of the examples. The pricing of options using normal mixture density functions to model returns; the use of Monte Carlo simulation to calculate the VaR of an options portfolio; modifying the covariance VaR to allow for fat-tailed P&L distributions; the calculation of implied, EWMA and 'historic' volatilities; GARCH volatility term structure forecasting; principal components analysis; and many more are all included.
Carol Alexander brings many new insights to the pricing and hedging of options with her understanding of volatility and correlation, and the uncertainty which surrounds these key determinants of option portfolio risk. Modelling the market risk of portfolios is covered where the main focus is on a linear algebraic approach; the covariance matrix and principal component analysis are developed as key tools for the analysis of financial systems. The traditional time series econometric approach is also explained with coverage ranging from the application cointegration to long-short equity hedge funds, to high-frequency data prediction using neural networks and nearest neighbour algorithms.
Throughout this text the emphasis is on understanding concepts and implementing solutions. It has been designed to be accessible to a very wide audience: the coverage is comprehensive and complete and the technical appendix makes the book largely self-contained.
Market Models: A Guide to Financial Data Analysis is the ideal reference for all those involved in market risk measurement, quantitative trading and investment analysis.


ßçûê: en

Ðóáðèêà: Ýêîíîìèêà è ôèíàíñû/

Ñòàòóñ ïðåäìåòíîãî óêàçàòåëÿ: Ãîòîâ óêàçàòåëü ñ íîìåðàìè ñòðàíèö

ed2k: ed2k stats

Ãîä èçäàíèÿ: 2001

Êîëè÷åñòâî ñòðàíèö: 494

Äîáàâëåíà â êàòàëîã: 19.09.2006

Îïåðàöèè: Ïîëîæèòü íà ïîëêó | Ñêîïèðîâàòü ññûëêó äëÿ ôîðóìà | Ñêîïèðîâàòü ID
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Ïðåäìåòíûé óêàçàòåëü
Risk measurement, factor models      229—248
Risk measurement, index stripping      238—239
Risk measurement, present value of a basis point move (PVBP)      256
Risk measurement, risk managers/asset managers      236—237
Risk measurement, time-varying parameter assumptions      238
Risk measurement, traditional measures      256—257
Risk, attitudes, modelling      194—198
Risk, certainty equivalence      194 195
Risk, correlation risk      138
Risk, decomposing risk      230—236
Risk, downside risk      258—259
Risk, financial markets      250—255
Risk, indifference      194 197—198
Risk, irreducible risk      9—10
Risk, market risk capital requirement (MRR)      251 252 253 254—255 274 276 279 280
Risk, return, relationship      189—193
Risk, risk premium      104 106
Risk, risk-free rate of return      21 23 104
Risk, risk-loving      195 198
Risk, sources of risk      232 256
Risk, transitive preferences      194
Risk, utility functions      194—196
Risk-adjusted performance measures (RAPM), capital allocation      193—194
Risk-adjusted performance measures (RAPM), information ratio (IR)      194
Risk-adjusted performance measures (RAPM), Sharpe ratio (SR)      194
Risk-adjusted returns, capital allocation      186 187
Risk-adjusted returns, traders, performance      186
Risk-free assets, minimum variance portfolios      192
Risk-free assets, risk/return      198
Risk-free assets, zero variance      231
Risk-neutrality, assumption      106
Risk-neutrality, certainty equivalence      195
Risk-neutrality, hypothesis      32
Risk-neutrality, local      81 106
Risk-neutrality, probability      81 106
Risk-neutrality, valuation      104 106
RiskMetrics data, covariance matrices      201—204
RiskMetrics data, covariance VaR models      260
RiskMetrics data, exponentially weighted moving average (EWMA)      60 115 163 179 202 203
RiskMetrics data, ghost features      204
RiskMetrics data, limitations      202—203
RiskMetrics data, methodology      179—180 201
RiskMetrics data, persistence      76 202
RiskMetrics data, reaction      202
RiskMetrics data, risk factors      202
RiskMetrics data, smoothing constant      202 203 204
RiskMetrics data, VaR (value-at-risk) models      102 203—204
RiskMetrics data, weighted average      179 201
Root mean square error (RMSE), distance metric      123
Root mean square error (RMSE), prediction      445
Root mean square error (RMSE), volatility forecasts      122—123
Rounding error, positive semi-definiteness      184
Russian debt crisis      35 251
S&P 500      86 89 129 155 202 231 234 371 403
S-Plus      84
Sampling error, constant volatility      52
Sampling error, exponentially weighted moving average (EWMA)      111
Sampling error, high frequency data      17
Sampling error, historic correlation      51
Sampling error, moving averages      63
Sampling error, ordinary least squares (OLS)      236
Sampling error, unconditional correlation      15 17
Sampling error, weighted average      49
Scatter plots      5 8 15 39 40
Scenario analysis, implied volatility      38—43 185
Scenario analysis, long-term volatility      92
Scenario analysis, market risk capital requirements (MRR)      253 279
Scenario analysis, principal component analysis (PCA)      39 143 144 154—155 282
Scenario analysis, probabilistic      280—281
Scenario analysis, risk management      34 38—43 141
Scenario analysis, skews      39 159
Scenario analysis, smile effect      39
Scenario analysis, VaR (value-at-risk) models      278—281
Scenario analysis, volatility term structures      92
Scenario analysis, yield curves      143
Schmidt — Phillips test      328
Sharpe ratio (SR)      194
Short sales, frontier analysis      186 191 198
Simulation, delta      105
Simulation, gamma      105
Simulation, historical simulation      267 268—270
Simulation, random numbers      105
Simulation, VaR (value-at-risk) models      267—274
Single outliers, alpha      96
Single outliers, beta      96
Single outliers, excess kurtosis      67
Skews, deviations      160—161
Skews, equity markets      155
Skews, implied volatility      1 30—31 32 33 68 155 158
Skews, jumpy markets      37—38 156
Skews, leverage effect      31 68
Skews, modelling      154—171
Skews, negative      30—31
Skews, parallel shifts      45
Skews, principal component analysis (PCA)      154—171
Skews, range-bounded markets      36 44 156
Skews, scenario analysis      39 159
Skews, trending markets      37 156
Skews, volatility clustering      66 67
Smile effect, implied volatility      1 30 32 33 98 155
Smile effect, modelling      154—171
Smile effect, option pricing      106—107 136
Smile effect, oversimplistic models      22
Smile effect, principal component analysis (PCA)      154—171
Smile effect, scenarios      39
Smile effect, smile fitting      106—107
Smile effect, volatility smile surface      33 81 106 107 143
Smoothing constant      115 117 163 202 203 204 217
Spot prices, cointegration      367
Spot prices, crude oil      55 60 78 111
Spot prices, hedging      27
Spot-future correlations, commodity markets      55
Spot-future correlations, Gulf War      55—56
Spread options      367
Square root of time rule, constant volatility      61
Square root of time rule, high frequency data      83
Square root of time rule, short-term horizons      97
Square root of time rule, volatility clustering      97
Squared returns, ARCH      83
Squared returns, autocorrelation      63 65—66 68 97
Squared returns, exponentially weighted moving average (EWMA)      57—58 207
Squared returns, regression      123 124
Squared returns, variance forecasts      123 124
Standard deviation, dispersion      4
Standard deviation, volatility forecasts      121
Standard error, hedging      139 140
Standard error, multicollinearity      172
Standard error, realized volatility      133
Standard error, regression      372
Standard error, variance estimators      127
Standard error, volatility estimators      127
Standard error, volatility forecasts      118—119 126
Standard Industrial Classification      233
Stationary processes, covariance stationarity      317—320
Stationary processes, jointly covariance stationary      14—15 341—344
Stationary processes, strict stationarity      317—320
Statistical factor models      235—236
Statistical inference, analysis of variance (ANOVA)      427—428
Statistical inference, confidence intervals      421—424
Statistical inference, f-tests      426—427
Statistical inference, hypothesis testing      421—424
Statistical inference, Lagrange multiplier (LM)      428
Statistical inference, likelihood ratio (LR)      428—429
Statistical inference, t-tests      424—426
Statistical inference, Wald test      428
Statistical volatility, confidence limits      29
Statistical volatility, exponentially weighted moving average (EWMA)      125
Statistical volatility, implied volatility distinguished      28—30
Statistical volatility, option pricing      29
Statistical volatility, volatility forecasts      118
Sticky models, delta      35 37
Sticky models, equity skew      45
Sticky models, fixed strike/ATM volatility      38
Sticky models, market regimes      36—38 44
Sticky models, strikes      35 36
Sticky models, trees      35 43
Sticky models, validation      156
Stochastic processes, asset return series      12
Stochastic processes, financial asset prices      1 3
Stochastic processes, GARCH models      98 105
Stochastic processes, option pricing      105
Stochastic processes, process volatility      11 22
Stochastic processes, random walk      351
Stochastic processes, stationary      12 317—320
Stochastic processes, trends      328
Stochastic volatility, diffusion limits      98
Stochastic volatility, financial asset returns      285
Stochastic volatility, large price changes      30
Stochastic volatility, option pricing      104 105
Stochastic volatility, perfect hedge      106
Stochastic volatility, risk-neutral probability      81
Straddles      118 124—125 386
Straights Times      89 90
Stress testing, covariance matrices      184—185
Stress testing, linear portfolios      185
Stress testing, risk management      141
Stress testing, VaR (value-at-risk) models      278 281—283
Strikes, discounted value      23 24
Strikes, fixed strike deviations      158 160 161
Strikes, fixed strike volatility      38 157 158 159—167
Strikes, implied volatility      26 27 28 30 31 32—33 155
Strikes, local volatility      34—35
Strikes, sticky strike model      35 36
Student t distributions      82 293
Symmetric GARCH      72—75 81—82 95 99 123
Systems of seemingly unrelated regression equations (SURE)      434—435
t-GARCH, Student t distributions      82
Term structures, cointegration      368
Term structures, futures prices      153—151
Term structures, kurtosis      303—305
Term structures, principal component analysis (PCA)      143 147—154
Threshold GARCH      81
Time series models, ARMA      see "Autoregressive moving average"
Time series models, autocorrelation      335—337
Time series models, autoregression      329—331
Time series models, basic properties      316—329
Time series models, correlogams      333—335
Time series models, detrending financial data      322—324
Time series models, Dickey — Fuller (DF) test      325—328
Time series models, integrated processes      320—322
Time series models, mean-reverting      317—320
Time series models, model identification      333—339
Time series models, moving averages      331—332
Time series models, multivariate      see "Multivariate time series"
Time series models, operators      316—317
Time series models, random walk      320—322
Time series models, RATS (Regression Analysis of Time Series)      80
Time series models, stationary processes      317—320
Time series models, statistical modelling      315—346
Time series models, testing down      337—338
Time series models, unit root test      324—327
Time series models, univariate      329—333
Time-varying correlation, bivariate GARCH      16
Time-varying correlation, conditional      see "Conditional correlation"
Time-varying correlation, correlation estimates      15 107
Time-varying correlation, GARCH models      16—17 108—114
Time-varying correlation, market betas      109 238
Time-varying correlation, optimal weights      112
Time-varying correlation, statistical hedge ratios      109
Time-varying variance      13 70 95
Time-varying volatility, actual/expected values      13
Time-varying volatility, conditional volatility      12 14
Time-varying volatility, GARCH models      14 95 115
Time-varying volatility, high frequency returns      17
Tracking models, benchmark tracking      144 172
Tracking models, cointegration      372
Tracking models, factor models      229
Tracking models, index tracking      172
Trading limits, risk aversion      186
Trading limits, short sales      186
Trading limits, VaR (value-at-risk) models      257
Trading performance, measurement      124
Trading strategy, implied volatility      125
Trading strategy, P&L      124 125
Transaction costs, long-term positions      29
Treasury bills      231
Trending markets, market regimes      36 37 44 156
TSP      84
Uncertainty, Black — Scholes model      23
Uncertainty, consequences      134—140
Uncertainty, correlation forecasts      137—138
Uncertainty, dynamically hedged portfolios      138—140
Uncertainty, marked-to-model value      136—138
Uncertainty, mixture of normal densities      136
Uncertainty, volatility      18 119
Unconditional correlation      15 17 49
Unconditional correlation matrices, principal component analysis (PCA)      147
Unconditional covariance, diagonal matrix      144 146 206
Unconditional covariance, principal component analysis (PCA)      162 206
Unconditional distribution, return process      12
Unconditional heteroscedasticity      432—433
Unconditional variance and volatility, I-GARCH      76
Unconditional variance and volatility, stationary series      12 317—320
Unconditional variance and volatility, weighted average      49—50
Underlying asset prices, ATM volatility      39
Underlying asset prices, constant volatility      22
Underlying asset prices, covariance      183
Underlying asset prices, geometric Brownian motion (GBM)      30
Underlying asset prices, implied volatility      11 26 183
Underlying asset prices, option hedging      10
Underlying asset prices, scenario analysis      185
Underlying asset prices, stochastic volatility      105
Underlying asset prices, volatility term structures      18
Unit root test      324—327 444
United States, alpha      91
United States, beta      91
United States, Dow Jones 30      231
United States, Microsoft      91—92
United States, Monopolies Commission      92
United States, persistence      86 91
United States, reaction      91
United States, S&P 500      86 89 129 155 202 231 234 371 403
United States, technology bubble      91
United States, USD      16 17 101—102 129—133
United States, zero-coupon bonds      148
Univariate GARCH      see "GARCH models"
Univariate time series models      329—333
Utility functions, expected utility      194—195
Utility functions, exponential utility function      196—197
Utility functions, investment analysis      185 194—197
Utility functions, logarithmic      196
Utility functions, marginal utility      195 197
Utility functions, mean-variance analysis      197
Utility functions, power utility function      196
Utility functions, quadratic      196
Utility functions, risk      194—196
Utility functions, risk aversion      195—196
Value, MtM      see "Marked-to-market (MtM) value"
VaR (value-at-risk) models, advantages/limitations      255—260
VaR (value-at-risk) models, alternatives      257—260
VaR (value-at-risk) models, backtesting      125 250 275—277
VaR (value-at-risk) models, conditional      259—260
VaR (value-at-risk) models, delta-gamma approximations      273—274
VaR (value-at-risk) models, extreme returns      185
VaR (value-at-risk) models, generalized extreme value (GEV)      293
VaR (value-at-risk) models, historical simulation      267 268—270
VaR (value-at-risk) models, marked-to-market (MtM) value      135
VaR (value-at-risk) models, market risk capital requirement (MRR)      253 254—255 274 276
VaR (value-at-risk) models, model validation      274—278
VaR (value-at-risk) models, Monte Carlo simulation      267 270—273 274 277—278
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